Bargaining Mechanism in Islamic Economic System

This article discusses the concept of bargaining position in the Islamic economic system. By using a literature study, this article finds a narrative that bargaining positions occur in goods or services. The conclusion are: bargaining must be carried out by more than one person. So, there are at least two people who transact (sellers and buyers). If there is only one person, the bargaining position certainly cannot happen. Examples of the many bargaining that occur are on the market. In a sale and purchase, those with higher bargaining rights are buyers. Whereas the seller will compensate the buyer for positive bargaining. Bidding is goods or services offered at a certain amount and price level and under certain conditions. There is also an offer in the Islamic economy that distinguishes it from conventional offers, that the goods or services offered must be transparent and specified in their specifications, how the condition of the goods, what are the advantages and disadvantages of the goods. The offer made does not harm the party submitting the request; and vice versa

FORETELL: Aggregating Distributed, Heterogeneous Information from Diverse Sources Using Market-based Techniques

Predicting the outcome of uncertain events that will happen in the future is a frequently indulged task by humans while making critical decisions. The process underlying this prediction and decision making is called information aggregation, which deals with collating the opinions of different people, over time, about the future event’s possible outcome. The information aggregation problem is non-trivial as the information related to future events is distributed spatially and temporally, the information gets changed dynamically as related events happen, and, finally, people’s opinions about events’ outcomes depends on the information they have access to and the mechanism they use to form opinions from that information. This thesis addresses the problem of distributed information aggregation by building computational models and algorithms for different aspects of information aggregation so that the most likely outcome of future events can be predicted with utmost accuracy. We have employed a commonly used market-based framework called a prediction market to formally analyze the process of information aggregation. The behavior of humans performing information aggregation within a prediction market is implemented using software agents which employ sophisticated algorithms to perform complex calculations on behalf of the humans, to aggregate information efficiently. We have considered five different yet crucial problems related to information aggregation, which include: (i) the effect of variations in the parameters of the information being aggregated, such as its reliability, availability, accessibility, etc., on the predicted outcome of the event, (ii) improving the prediction accuracy by having each human (software-agent) build a more accurate model of other humans’ behavior in the prediction market, (iii) identifying how various market parameters effect its dynamics and accuracy, (iv) applying information aggregation to the domain of distributed sensor information fusion, and, (v) aggregating information on an event while considering dissimilar, but closely-related events in different prediction markets. We have verified all of our proposed techniques through analytical results and experiments while using commercially available data from real prediction markets within a simulated, multi-agent based prediction market. Our results show that our proposed techniques for information aggregation perform more efficiently or comparably with existing techniques for information aggregation using prediction markets

Bidding Strategies in Agent-based Continuous Double Auctions

Online auctions are a platform to trade goods on the Internet. In this context, negotiation capabilities for software agents in continuous double auctions (CDAs) are a central concern. Agents need to be able to prepare bids for and evaluate offers on behalf of the users they represent with the aim of obtaining the maximum benefit for their users. For the agents, their bids are decided according to some bidding strategy. However, in CDAs, it is a complex decision problem because of the inherent uncertainty and dynamics of the auction market. In this book, we present a new bidding strategy for agents to adopt in CDAs and propose tools to enhance the performance of existing bidding strategies in CDAs. The superior performance of the new bidding strategy as well as the tools presented in this book are illustrated through extensive experiments

Bidding Strategies in Agent-based Continuous Double Auctions

Online auctions are a platform to trade goods on the Internet. In this context, negotiation capabilities for software agents in continuous double auctions (CDAs) are a central concern. Agents need to be able to prepare bids for and evaluate offers on behalf of the users they represent with the aim of obtaining the maximum benefit for their users. For the agents, their bids are decided according to some bidding strategy. However, in CDAs, it is a complex decision problem because of the inherent uncertainty and dynamics of the auction market. In this book, we present a new bidding strategy for agents to adopt in CDAs and propose tools to enhance the performance of existing bidding strategies in CDAs. The superior performance of the new bidding strategy as well as the tools presented in this book are illustrated through extensive experiments